Electronic learning (e-learning) and educational training in today's healthcare industry tend to focus on passive learning based on a linear presentation of medical information and a subsequently serialized testing of the presented medical information. For example, in a conventional method of presenting clinical training information over a computerized interface, a medical student, a paramedic trainee, a nursing trainee, or another healthcare industry professional is typically presented with linearly-broadcasted medical information that lacks interactive, hands-on, and empirical clinical training experience.
Unfortunately, the linearly-broadcasted medical information presented to a healthcare trainee is often detached from the reality of clinical practice, especially in case of diagnostic reasoning and differential diagnosis training for patient conditions and symptoms. In real-life clinical practice, a seasoned physician relies on his or her clinical knowledge and experience to conduct a time-efficient and educated guess for identifying a particular disease. In most circumstances, the seasoned physician does not linearly and exhaustively search through all possible differential diagnosis to identify the particular disease. The ability to identify a patient's disease correctly, based on one's own clinical knowledge and experience, is called “dynamic DDx,” or dynamic differential diagnosis. Conventional e-learning products in the healthcare industry are unable to instill trainees with dynamic differential diagnosis reasoning skills, which is an invaluable skill set in real-life clinical practice for an effective and rapid patient diagnosis.
Furthermore, conventional e-learning systems do not provide healthcare trainees with an integrated and simulated patient diagnosis training and evaluation interface that allows the healthcare trainees to nurture or test any skill set associated with dynamic differential diagnosis reasoning In addition, conventional e-learning systems do not provide the healthcare trainees with a robust training guidance and feedback provided by a healthcare education expert.
Therefore, it may be desirable to provide a dynamic differential diagnosis training and evaluation system and a related method for patient condition determination. Furthermore, it may also be desirable to provide a dynamic differential diagnosis training and evaluation system and a related method that enable testing and evaluation of a healthcare trainee's dynamic differential diagnosis reasoning skills for patient condition determination.
Moreover, it may also be desirable to provide an e-learning system that provides a robust training guidance and evaluation feedback conceived by a healthcare education expert who utilizes a robust set of clinical research data linked to a healthcare content authoring platform.